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Rapid Flood Inundation Forecast Using Fourier Neural Operator
Flood inundation forecast provides critical information for emergency planning before and during flood events.
Applications of physics-informed scientific machine learning in subsurface science: A survey
Geosystems are geological formations altered by humans activities such as fossil energy exploration, waste disposal, geologic carbon sequestration, and renewable energy generation.
Combining Physically-Based Modeling and Deep Learning for Fusing GRACE Satellite Data: Can We Learn from Mismatch?
Global hydrological and land surface models are increasingly used for tracking terrestrial total water storage (TWS) dynamics, but the utility of existing models is hampered by conceptual and/or data uncertainties related to various underrepresented and unrepresented processes, such as groundwater storage.
Discovering state-parameter mappings in subsurface models using generative adversarial networks
A fundamental problem in geophysical modeling is related to the identification and approximation of causal structures among physical processes.
